Final Project of the Udacity AI Programming with Python Nanodegree
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Updated
Aug 16, 2018 - Jupyter Notebook
Final Project of the Udacity AI Programming with Python Nanodegree
A set of Python scripts to evaluate the Automotive Datasets provided by Prophesee
🏆 A Comparative Study on Handwritten Digits Recognition using Classifiers like K-Nearest Neighbours (K-NN), Multiclass Perceptron/Artificial Neural Network (ANN) and Support Vector Machine (SVM) discussing the pros and cons of each algorithm and providing the comparison results in terms of accuracy and efficiecy of each algorithm.
AI Learning Hub for Machine Learning, Deep Learning, Computer Vision and Statistics
In depth machine learning resources
A speculative mechanism to accelerate long-latency off-chip load requests by removing on-chip cache access latency from their critical path, as described by MICRO 2022 paper by Bera et al. (https://arxiv.org/pdf/2209.00188.pdf)
Implementations of machine learning algorithm by Python 3
Implementation of single layer perceptron algorithm in Python
Artificial Neural Network designed with Tensorflow that classifies UDP data set into DDoS data set and normal traffic data set.
A single artificial neuron built from scratch to understand the maths behind neural nets !
This is the implementation of perceptron learning algorithm.
Homework solutions of Intro to ML course at MIT Spring 2018
MLP BP vs SVM and SOM Neural Net implementation to predict hypertension
Python implementations of several Machine Learning algorithms.
Implemented modern last-level cache(LLC) with the concept of "Perceptron Learning for Reuse Prediction" that use neural network idea, which is training the predictor by a smaller independent cache with a series of features.
Machine Learning algorithms built from scratch for AMMI Machine Learning course
Python implementation of the simple perceptron or also known as a single-layer neural network, is a binary classification algorithm by Frank Rosenblatt based on the neural model of Warren McCulloch and Walter Pitts developed in 1943.
Implementation of Perceptron as coursework for Artificial Intelligence course @ PUC Minas
In this project, I used Hebbian, Perceptron, Adaline, MultiClassPerceptron and MultiClassAdaline neural networks to implement X and O character recognition.
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